

*** Reliability as Resovle: Reputational Transferance in International Relations
*** Md Muhibbur Rahman
*** January 2026



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****************************************************************** Main Text *********************************************************************************** 
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use jpr_replication_data, clear 
xtset id year 

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***** Models in the main text 


*** Table 1 – Logistic Regression Models

logit dispute L.poor_rep_t_def peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m1
logit dispute L.poor_rep_t_def ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m2
logit dispute L.poor_rep_t_def peaceyrs peaceyrs2 peaceyrs3 if ptargdef==1, vce(robust)
estimates store m3
logit dispute L.poor_rep_t_def pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3 if ptargdef==1, vce(robust)
estimates store m4

esttab m1 m2 m3 m4 using tab1.tex, tex replace ///
    se r2 varwidth(30) label ///
    star(† 0.10 * 0.05 ** 0.01 *** 0.001) 



*** Table 2 – Two-way Fixed Effects Models

xtreg dispute L.poor_rep_t_def i.year, fe 
estimates store m5
xtreg dispute L.poor_rep_t_def ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war i.year, fe
estimates store m6
xtreg dispute L.poor_rep_t_def i.year if ptargdef==1, fe
estimates store m7
xtreg dispute L.poor_rep_t_def pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war i.year if ptargdef==1, fe 
estimates store m8

esttab m5 m6 m7 m8 using tab2.tex, tex replace ///
    drop(*.year) ///
    se r2 varwidth(30) label ///
    star(† 0.10 * 0.05 ** 0.01 *** 0.001) 


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***** Figures in the main text 


*** Figure 1. Distribution of the Reputation Variable 
*- See Jupyter Notebook (Python) Code file: "figure_1_code"



*** Figure 2. Marginal Effects on MID Initiation (Challenger) 
*- See Jupyter Notebook (Python) Code file: "figure_2_code"



*** Figure 3. Pretreatment Trends (GTATE) 
*- See Jupyter Notebook (Python) Code file: "figure_3_and_4_code"



*** Figure 4. Average Treatment Effects on the Treated 
*- See Jupyter Notebook (Python) Code file: "figure_3_and_4_code"





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*************************************************************** Online Appendix ******************************************************************************** 
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use jpr_replication_data, clear 
xtset id year 

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****** Models in the Appendix


*** Table A1– Summary statistics

estpost sum dispute dispute_hh3 dispute_hh4 poor_rep_t_def poor_rep_t_all ptargdef pchaloff pchalneu defense_ally capprop majorpower jdem s_un_glo ln_distance cold_war

esttab using dst1.tex, cell((count mean sd min max)) b(3) varwidth(30)



*** Table A2 – Logistic Regression Models: Reputation Not Lagged

logit dispute poor_rep_t_def peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m13
logit dispute poor_rep_t_def ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m14
logit dispute poor_rep_t_def peaceyrs peaceyrs2 peaceyrs3 if ptargdef==1, vce(robust)
estimates store m15
logit dispute poor_rep_t_def pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3 if ptargdef==1, vce(robust)
estimates store m16

esttab m13 m14 m15 m16 using tab3.tex, tex replace ///
    se r2 varwidth(30) label ///
    star(† 0.10 * 0.05 ** 0.01 *** 0.001) 



*** Table A3 – Logistic Regression Models: Controlling for Intra-Alliance MIDs and Interwar Period

* controling for intra alliance MIDs
logit dispute L.poor_rep_t_def ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war defense_ally peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m17
logit dispute L.poor_rep_t_def pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war defense_ally peaceyrs peaceyrs2 peaceyrs3 if ptargdef==1, vce(robust)
estimates store m18

* controling for interwar MIDs
logit dispute L.poor_rep_t_def ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war interwar peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m19
logit dispute L.poor_rep_t_def pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war interwar peaceyrs peaceyrs2 peaceyrs3 if ptargdef==1, vce(robust)
estimates store m20

esttab m17 m18 m19 m20 using tab4.tex, tex replace ///
    se r2 varwidth(30) label ///
    star(† 0.10 * 0.05 ** 0.01 *** 0.001) 



*** Table A4 – Logistic Regression Models: Higher-level MIDs

logit dispute_hh3 L.poor_rep_t_def ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m21
logit dispute_hh4 L.poor_rep_t_def ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m22
logit dispute_hh3 L.poor_rep_t_def pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3 if ptargdef==1, vce(robust)
estimates store m23
logit dispute_hh4 L.poor_rep_t_def pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3 if ptargdef==1, vce(robust)
estimates store m24

esttab m21 m22 m23 m24 using tab5.tex, tex replace ///
    se r2 varwidth(30) label ///
    star(† 0.10 * 0.05 ** 0.01 *** 0.001) 



*** Table A5 – Logistic Regression Models: Reputation Based on All Alliance Types

logit dispute L.poor_rep_t_all peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m25
logit dispute L.poor_rep_t_all ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war peaceyrs peaceyrs2 peaceyrs3, vce(robust)
estimates store m26

esttab m25 m26 using tab6.tex, tex replace ///
    se r2 varwidth(30) label ///
    star(† 0.10 * 0.05 ** 0.01 *** 0.001) 


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*** Table A6 – TWFE Models: Reputation Based on All Alliance Types

xtreg dispute L.poor_rep_t_all i.year, fe 
estimates store m27
xtreg dispute L.poor_rep_t_all ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war i.year, fe
estimates store m28

esttab m27 m28 using tab7.tex, tex replace ///
    drop(*.year) ///
    se r2 varwidth(30) label ///
    star(† 0.10 * 0.05 ** 0.01 *** 0.001) 


*** Table A7 – TWFE Models: PlaceboTests

set seed 123

* With randomly assigned treatment
gen random_treatment = runiform() > 0.1
xtreg dispute i.random_treatment ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war i.year, fe
estimates store m29

* Psuedo outcome variable 
gen random_outcome = runiform() > 0.1
xtreg random_outcome L.poor_rep_t_def ptargdef pchaloff pchalneu capprop majorpower jdem s_un_glo ln_distance cold_war i.year, fe
estimates store m30

esttab m29 m30 using tab8.tex, tex replace ///
    drop(*.year) ///
    se r2 varwidth(30) label ///
    star(† 0.10 * 0.05 ** 0.01 *** 0.001) 


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